Senior Software Engineer - Motion Planning, Secondary Driving System

Description

The company's product teams design vehicles and experiences around people, combining hardware, battery systems, design, software, and safety and entertainment features.

The Embodied AI teams build driver assistance and automated driving systems that pair human-centered design with robotics, optimization, and machine learning, aiming for systems that are intelligent, intuitive, and trustworthy.

The Secondary Driving System (SDS) is an independent stack of perception, planning, and controls. If the primary driving system becomes unavailable, SDS keeps the vehicle operating safely for a limited time, asks the driver to take over, and when needed carries out a Minimal Risk Maneuver (MRM) to bring the vehicle to a safe stop. You will join the SDS team within Embodied AI.

Responsibilities

• Build production-quality C++ across the SDS stack, combining ML-based perception (object detection, tracking, prediction, lane and road features) with analytical planners and classical controllers under tight latency and compute limits.
• Design and implement planning and control algorithms for SDS, including lane keeping, obstacle avoidance, lane changes to the shoulder, and controlled stops for MRM scenarios with limited operating horizons.
• Work as a senior individual contributor across the autonomy stack, focusing on motion planning and controls in a robotics setting, so SDS can handle faults and reach a minimal risk condition when the primary system cannot.
• Own features from start to finish: clarify requirements, lead design reviews, implement, bring up in simulation and hardware-in-the-loop, test on the road, and iterate using metrics and driver feedback.
• Define and implement interfaces and contracts with state estimation, mapping, localization, and autonomy management teams so SDS engages reliably when the primary stack fails.
• Work with perception, state estimation, vehicle dynamics, systems engineering, and safety experts to deliver robust fail-operational behavior for the company's current and future products.
• Partner with safety and systems engineering to keep SDS behavior and software designs aligned with functional safety, redundancy, and MRM requirements for fail-operational eyes-off features.
• Analyze and debug integration issues across perception, planning, controls, and vehicle behavior using logs, telemetry, and controlled experiments.
• Apply engineering best practices: clean interfaces, code review, automated testing, continuous integration, performance profiling, and observability for on-road incidents.
• Mentor engineers through design discussions, code reviews, and example implementations, helping the team raise robustness, clarity, and execution speed.

Requirements

• Must-Have: a BS, MS, or PhD in computer science, robotics, electrical or mechanical engineering, or a related field, or equivalent practical experience.
• Must-Have: 3+ years of professional software engineering building production systems in robotics, autonomous vehicles, or complex real-time or control systems.
• Must-Have: strong modern C++ (C++14/17 or later) on large codebases with many contributors, plus familiarity with Python for tooling, prototyping, and data analysis.
• Must-Have: experience in motion planning and controls, including trajectory generation and tracking; optimal control, model-predictive control, or trajectory optimization; classical and modern feedback control design (e.g., PID, LQR, robust control); and handling kinematic and dynamic constraints for ground vehicles.
• Must-Have: experience integrating with perception and prediction pipelines (object detection, tracking, prediction, lane or road geometry), even if planning and controls is your core focus.
• Must-Have: a record of delivering reliable, high-quality autonomy or robotics software, with testing strategies, metrics, and performance tuning under latency and compute constraints.
• Must-Have: strong communication and collaboration across ML, systems, platform, and safety teams, and the ability to bring clarity to ambiguous technical problems.
• Must-Have: a passion for automated driving and robotics, and for building systems that measurably improve safety and driver experience.
• Nice-to-Have: background in ROS or similar robotics middleware.
• Nice-to-Have: experience with safety-critical software or close work with functional safety teams.
• Nice-to-Have: hands-on experience with GPU or accelerator-based ML inference, model deployment, and performance optimization in production.
• Nice-to-Have: the same degree and 3+ years of professional experience requirements also appear in this preferred list.

Conditions

The salary range for the L7 (senior) role is $170,600.00 to $261,300.00. The actual base salary offered within this range depends on factors relevant to the position.

This pay range is a good faith estimate only, based on what a successful applicant might be paid under applicable state laws, and may not represent roles located outside the California Bay Area.

The role is remote. If the selected candidate lives within a specific mile radius of a company hub, they will be expected to report there three times a week, or at another frequency set by their manager.

Relocation benefits are available for candidates who qualify under company policy.

Applicants may be required, where applicable, to complete a role-related assessment and/or a pre-employment screening before starting.

The company is committed to a workplace free of unlawful discrimination that actively fosters inclusion and belonging.

Benefits

• Health and wellbeing programs include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, sickness and accident benefits, life insurance, and employee assistance.
• Also available: retirement savings plan, paid vacation and holidays, tuition assistance, company vehicle discounts, and more.
• An incentive pay program pays out based on company performance, job level, and individual performance.
• Relocation support is available for candidates who qualify under company policy.